Abstract
This correspondence deals with the problem of estimating average signal-to-noise ratio (SNR) for a communication link employing binary frequency shift keying (BFSK) in the presence of a carrier frequency offset (CFO). The transmitted symbols are corrupted by Rayleigh fading and additive white Gaussian noise (AWGN). We treat the CFO as a nuisance parameter and estimate it using a data statistics based estimator. This estimate is then used to design a maximum likelihood (ML) estimator to get the estimates of SNR. We also derive the Cramér-Rao bound (CRB) for the estimators and have shown the performance of both the data-aided and non-data-aided estimators.
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